We evaluated the reliability and clinical value of amide proton transfer-weighted (APTW) MR imaging at 3 Tesla in adult gliomas. Fifty-seven patients with primary gliomas were recruited and scanned. Two radiologists evaluated the location and size of the APTW hyperintensity and enhancing areas, and measured the tumor and contralateral normal-appearing white matter (CNAWM) APTW values. The correlation between relative APTW (rAPTW) values and pathologic grades was calculated. Results showed APTW analysis had good reliability. APTW images almost showed the same compared with T1-weighted contrast-enhancing (T1W+C) images. The tumor rAPTW values had a strong positive correlation with pathologic grades.
Fifty-seven patients with primary gliomas were recruited and scanned, including 23 cases of grade IV; 12 cases of grade III; 21 cases of grade II; and only 1 case of grade I, based on the World Health Organization (WHO) standard (2007/2016).
For the qualitative analysis, two experienced radiologists (blinded to the pathology diagnosis) determined the APTW signal features, and compared the location and size of the APTW hyperintensity and enhancing T1W areas (Fig. 1 A1,2). Kappa coefficient was used to evaluate the reliability of their results. A third radiologist would join the analysis when there were any disagreements.
For the quantitative APTW measurements, two observers independently drew (blinded to the pathology diagnosis) six ROIs on each glioma mass, depending upon the T1WI contrast-enhancement and APTW signals. The CNAWM APTW values were also recorded (Fig.1 B1~6). The maximum, minimum, and mean APTW values from these six ROIs were recorded as APTWmax, APTWmin, and APTWmean. We calculated the relative values (rAPTW) by subtracting the CNAWM APTW values from the absolute APTW values and recorded them as rAPTWmax, rAPTWmin, and rAPTWmean. Intraclass correlation coefficients (ICCs) were used to evaluate the reliability of rAPTWmax, rAPTWmin, and rAPTWmean measurements. Multivariate logistic regression model was used to explore the correlation between the rAPTW values and pathologic grades. We applied ROC curves to get the cut-off rAPTW values in differentiating the HGGs from LGGs, and the sensitivity, specificity, accuracy were calculated at the same time.
For the qualitative analysis of the APTW and T1W+C images, we compared the lesions with or without APTW hyperintensity and estimated the location and size between the APTW hyperintensity and enhancing areas, and then we got the Kappa values of 0.838, 0.632 and 0.925, respectively. At least 75.4% (43/57) APTW images showed the same tumor features as T1W+C images (Fig. 2). The APTW signals of the liquid in the tumor cavities were variable, some were hyperintensity while others were hypointensity.
For the quantitative measurements of the ROIs, the ICCs for the rAPTWmax, rAPTWmin, and rAPTWmean values measured by two observers were 0.944, 0.872, and 0.944, respectively. There was a strong positive correlation between the glioma tumor rAPTW values and pathologic grades (Fig. 3 A). These rAPTW parameters of the glioma tumors had high collinearity. We found that rAPTWmax was the most relevant one to the grades, with the 95% confidence interval (CI) in subdividing the gliomas into I~IV grades to be 1.66%, 1.67%~2.57%, 2.73%~3.52%, and 3.43%~4.05%, respectively. The area under ROC curve (AUC) of rAPTWmax was 0.886 (Fig. 3 B) in differentiating the HGGs from LGGs, with a cut-off value of 2.46% (sensitivity 94.3%, specificity 81.8%, and accuracy 87.7%).